Efficiency of nitrogen fertilizer applied at corn sowing in contrasting growing seasons in Paraguay

In order to select soil management practices that increase the nitrogen-use efficiency (NUE) in agro-ecosystems, the different indices of agronomic fertilizer efficiency must be evaluated under varied weather conditions. This study assessed the NUE indices in no-till corn in southern Paraguay. Nitrogen fertilizer rates from 0 to 180 kg ha-1 were applied in a single application at corn sowing and the crop response investigated in two growing seasons (2010 and 2011). The experimental design was a randomized block with three replications. Based on the data of grain yield, dry matter, and N uptake, the following fertilizer indices were assessed: agronomic N-use efficiency (ANE), apparent N recovery efficiency (NRE), N physiological efficiency (NPE), partial factor productivity (PFP), and partial nutrient balance (PNB). The weather conditions varied largely during the experimental period; the rainfall distribution was favorable for crop growth in the first season and unfavorable in the second. The PFP and ANE indices, as expected, decreased with increasing N fertilizer rates. A general analysis of the N fertilizer indices in the first season showed that the maximum rate (180 kg ha-1) obtained the highest corn yield and also optimized the efficiency of NPE, NRE and ANE. In the second season, under water stress, the most efficient N fertilizer rate (60 kg ha-1) was three times lower than in the first season, indicating a strong influence of weather conditions on NUE. Considering that weather instability is typical for southern Paraguay, anticipated full N fertilization at corn sowing is not recommended due the temporal variability of the optimum N fertilizer rate needed to achieve high ANE.

Genotypic variability in seed accumulation of foliar-applied molybdenum to common bean

The genotypic variability in molybdenum (Mo) accumulation in common bean seeds has been demonstrated in cases in which soil is the main Mo source, but this variability is yet unknown when Mo is foliar-applied. Therefore, seed Mo concentrations (SMoCc) and seed Mo contents (SMoCt) of 12 genotypes were determined in four experiments in the Zona da Mata, Minas Gerais, Brazil, in which plants were sprayed with 600 g ha-1 Mo. For comparison, two additional experiments without external Mo were conducted. Without Mo application, the average SMoCc was undetectable or 2.83 µg g-1, without significant differences among genotypes. On average, with Mo applications, SMoCc ranged from 14.7 to 25.0 µg g-1 and SMoCt, from 3.94 to 6.84 µg. 'Majestoso' was among the genotypes with the highest SMoCc in the four experiments. However, the large-seeded 'Jalo MG-65' and 'Carnaval' generally had higher SMoCt than the small-seeded 'Majestoso'. 'Ouro Negro' and especially 'Valente' were among the genotypes with the lowest SMoCc and SMoCt. The values of these variables were 61 and 90 %, respectively, higher for 'Majestoso' than those for 'Valente'. Our results suggest that common bean genotypes differ in their capacity to accumulate foliar-applied Mo in the seeds. Mo-rich seeds of large-seeded genotypes or of small-seeded of small-seeded genotypes with good capacity to accumulate Mo in seeds can be produced with relatively less Mo fertilizer.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

Multivariate analysis applied to the study of the relationship between soil and plant properties in a peach orchard

In the State of Rio Grande do Sul, the municipality of Pelotas is responsible for 90 % of peach production due to its suitable climate and soil conditions. However, there is the need for new studies that aim at improved fruit quality and increased yield. The aim of this study was to evaluate the relationship that exists between soil physical properties and properties in the peach plant in the years 2010 and 2011 by the technique of multivariate canonical correlation. The experiment was conducted in a peach orchard located in the municipality of Morro Redondo, RS, Brazil, where an experimental grid of 101 plants was established. In a trench dug beside each one of the 101 plants, soil samples were collected to determine silt, clay, and sand contents, soil density, total porosity, macroporosity, microporosity, and volumetric water content in the 0.00-0.10 and 0.10-0.20 m layers, as well as the depth of the A horizon. In each plant and in each year, the following properties were assessed: trunk diameter, fruit size and number of fruits per plant, average weight of the fruit per plant, fruit pulp firmness, Brix content, and yield from the orchard. Exploratory analysis of the data was undertaken by descriptive statistics, and the relationships between the physical properties of the soil and of the plant were assessed by canonical correlation analysis. The results showed that the clay and microporosity variables were those that exhibited the highest coefficients of canonical cross-loading with the plant properties in the soil layers assessed, and that the variable of mean weight of the fruit per plant was that which had the highest coefficients of canonical loading within the plant group for the two years assessed.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).

Analysis of joint laxity after total ankle arthroplasty: cadaver study.

BACKGROUND: Clinical results of total ankle arthroplasty with early designs were disappointing. Recently-developed ankle prostheses have good mid-term results; however, limited information is available regarding effects of total ankle arthroplasty on ankle laxity. METHODS: Eight cadaveric lower extremities were tested with a custom device which enabled measurement of multi-axial forces, moments, and displacement during applied axial, shear, and rotational loading. Tests consisted of anterior-posterior and medial-lateral translation and internal-external rotation of the talus relative to the tibia during axial loads on the tibia simulating body weight (700 N) and an unloaded condition (5 N). Tests were performed in neutral, dorsiflexion, and plantarflexion. Laxity was determined for the intact ankle, and following insertion of an unconstrained total ankle implant, comparing load-displacement curve. FINDINGS: Laxity after total ankle arthroplasty did not approximate the normal ankle in most conditions tested. Displacement was significantly greater for total ankle arthroplasty in both posterior and lateral translation, and internal rotation, with 5 N axial loading, and anterior-posterior, medial-lateral translation, and internal-external rotation for 700 N axial loading. For the 700 N axial load condition, in the neutral ankle position, total anterior-posterior translation averaged 0.4 mm (SD 0.2 mm), but 6.0 mm (SD 1.5 mm) after total ankle arthroplasty (P<0.01). This study demonstrated more laxity in the replaced ankle than normal ankle for both unloaded and 700 N axially loaded conditions. INTERPRETATION: These data indicate the increased responsibility of the ligaments for ankle laxity after total ankle arthroplasty and suggest the importance of meticulous ligament reconstruction with total ankle arthroplasty operations.

Building a Social Accounting Matrix within the ESA95 Framework: Obtaining a Dataset for Applied General Equilibrium Modelling

This research provides a description of the process followed in order to assemble a "Social Accounting Matrix" for Spain corresponding to the year 2000 (SAMSP00). As argued in the paper, this process attempts to reconcile ESA95 conventions with requirements of applied general equilibrium modelling. Particularly, problems related to the level of aggregation of net taxation data, and to the valuation system used for expressing the monetary value of input-output transactions have deserved special attention. Since the adoption of ESA95 conventions, input-output transactions have been preferably valued at basic prices, which impose additional difficulties on modellers interested in computing applied general equilibrium models. This paper addresses these difficulties by developing a procedure that allows SAM-builders to change the valuation system of input-output transactions conveniently. In addition, this procedure produces new data related to net taxation information.

Melt variability in percolated peridotite: an experimental study applied to reactive migration of tholeiitic basalt in the upper mantle

Melt-rock reaction in the upper mantle is recorded in a variety of ultramafic rocks and is an important process in modifying melt composition on its way from the source region towards the surface. This experimental study evaluates the compositional variability of tholeiitic basalts upon reaction with depleted peridotite at uppermost-mantle conditions. Infiltration-reaction processes are simulated by employing a three-layered set-up: primitive basaltic powder ('melt layer') is overlain by a 'peridotite layer' and a layer of vitreous carbon spheres ('melt trap'). Melt from the melt layer is forced to move through the peridotite layer into the melt trap. Experiments were conducted at 0.65 and 0.8 GPa in the temperature range 1,170-1,290 degrees C. In this P-T range, representing conditions encountered in the transition zone (thermal boundary layer) between the asthenosphere and the lithosphere underneath oceanic spreading centres, the melt is subjected to fractionation, and the peridotite is partially melting (T (s) similar to 1,260 degrees C). The effect of reaction between melt and peridotite on the melt composition was investigated across each experimental charge. Quenched melts in the peridotite layers display larger compositional variations than melt layer glasses. A difference between glasses in the melt and peridotite layer becomes more important at decreasing temperature through a combination of enrichment in incompatible elements in the melt layer and less efficient diffusive equilibration in the melt phase. At 1,290A degrees C, preferential dissolution of pyroxenes enriches the melt in silica and dilutes it in incompatible elements. Moreover, liquids become increasingly enriched in Cr(2)O(3) at higher temperatures due to the dissolution of spinel. Silica contents of liquids decrease at 1,260 degrees C, whereas incompatible elements start to concentrate in the melt due to increasing levels of crystallization. At the lowest temperatures investigated, increasing alkali contents cause silica to increase as a consequence of reactive fractionation. Pervasive percolation of tholeiitic basalt through an upper-mantle thermal boundary layer can thus impose a high-Si 'low-pressure' signature on MORB. This could explain opx + plag enrichment in shallow plagioclase peridotites and prolonged formation of olivine gabbros.

The total material requirement -concept applied to agriculture : a case study from Finland

Selostus: Luonnonvarojen kokonaiskäyttö sovellettuna maatalouteen: esimerkki Suomesta

Response of Iowa Pavements to Heavy Agricultural Loads, HR-1075, 1999

Iowa's county road system includes several thousands of miles of paved roads which consist of Portland cement concrete (PCC) surfaces, asphalt cement concrete (ACC) surfaces, and combinations of thin surface treatments such as seal coats and slurries. These pavements are relatively thin pavements when compared to the state road system and therefore are more susceptible to damage from heavy loads for which they were not designed. As the size of the average farm in Iowa has increased, so have the size and weights of implements of husbandry. These implements typically have fewer axles than a truck hauling the same weight would be required to have; in other words, some farm implements have significantly higher axle weights than would be legal for semi-trailers. Since stresses induced in pavements are related to a vehicle's axle weight, concerns have been raised among county and state engineers regarding the possible damage to roadway surfaces that could result from some of these large implements of husbandry. Implements of husbandry on Iowa's highway system have traditionally not been required to comply with posted weight embargo on bridges or with regulations regarding axle-weight limitations on roadways. In 1999, with House File 651, the Iowa General Assembly initiated a phased program of weight restrictions for implements of husbandry. To help county and state engineers and the Iowa legislature understand the effects of implements of husbandry on Iowa's county roads, the following study was conducted. The study investigated the effects of variously configured grain carts, tank wagons, and fence-line feeders on Iowa's roadways, as well as the possible mitigating effects of flotation tires and tracks on the transfer of axle weights to the roadway. The study was accomplished by conducting limited experimental and analytical research under static loading conditions